Tourist Choice Processing: Evaluating Decision Rules and Methods of Their Measurement
本研究采用贪心分析（greedoid analysis）方法估计非补偿性决策规则（LBA），并与旅游研究中常用的加权加总模型（WADD）比较，发现LBA在解释受访者偏好顺序上表现更好，但样本外预测精度较低。
A detailed understanding of decision rules is essential in order to better explain consumption behavior, yet the variety of decision rules used have been somewhat neglected in tourism research. This study adopts an innovative method, greedoid analysis, to estimate a noncompensatory type of decision rule known as lexicographic by aspect (LBA). It is quite different from the weighted additive (WADD) model commonly assumed in tourism studies. By utilizing an experimental research design, this study enables the evaluation of the two types of decision rules regarding their predictive and explanatory power. Additionally, we introduce a novel evaluation indicator (“cost”), which allows further investigation of the heterogeneity in the use of decision rules. The results suggest that although the out-of-sample accuracy is lower, the LBA model has a better explanatory performance on respondents’ preference order. Moreover, the different perspective provided by the LBA model is useful for obtaining managerial implications.